Reliability Analysis for Asset Management of Electric Power Grids

This book is an update and expansion of topics covered in Guidelines for Mechanical Integrity Systems (2006). The new book is consistent with Risk-Based Process Safety and Life Cycle approaches and includes details on failure modes and mechanisms. Also, example testing an inspection programs is included for various types of equipment and systems. Guidance and examples are provided for selecting and maintaining critical safety systems.

In the Handbook of Asset and Liability Management: From Models to Optimal Return Strategies, Alexandre Adam presents a comprehensive guide to Asset and Liability Management. Written from a quantitative perspective with economic explanations, this book will appeal to both mathematicians and non-mathematicians alike as it gives an operational view on the business. Well structured, this book includes essential information on Balance Sheet Items and Products Modeling, Tools for Asset and Liability Managers, as well as Optimal Returns Strategies. Explaining, in detail, all the written and unwritten rules of Asset Liability Management, using up-to-date models and the latest findings, the Handbook of Asset and Liability Management is an essential tool for Asset and Liability Managers both for the present day and the future.

Comprehensive and practical, Pavement Asset Management provides an essential resource for educators, students and those in public agencies and consultancies who are directly responsible for managing road and airport pavements. The book is comprehensive in the integration of activities that go into having safe and cost-effective pavements using the best technologies and management processes available. This is accomplished in seven major parts, and 42 component chapters, ranging from the evolution of pavement management to date requirements to determining needs and priority programming of rehabilitation and maintenance, followed by structural design and economic analysis, implementation of pavement management systems, basic features of working systems and finally by a part on looking ahead. The most current methodologies and practical applications of managing pavements are described in this one-of-a-kind book. Real world up-to-date examples are provided, as well as an extensive list of references for each part.

A practical approach to the mathematical tools needed to increase portfolio growth, learn successful trading strategies, and manage the risks associated with market fluctuation Mathematical Asset Management presents an accessible and practical introduction to financial derivatives and portfolio selection while also acting as a basis for further study in mathematical finance. Assuming a fundamental background in calculus, real analysis, and linear algebra, the book uses mathematical tools only as needed and provides comprehensive, yet concise, coverage of various topics, such as: Interest rates and the connection between present value and arbitrage Financial instruments beyond bonds that serve as building blocks for portfolios Trading strategies and risk performance measures Stochastic properties of stock prices The difference between expected return and expected growth and the geometric Brownian motion Diversification through the creation of optimal portfolios under various constraints The use of the Capital Asset Pricing Model to accurately estimate the difference between the return of the market and the short rate To further demonstrate the reality of the discussed concepts, the author analyzes five active stocks over a four-year period and highlights the different methods and portfolios that exist in today's economic world. Exercises are also provided throughout the text, along with the solutions, allowing readers to measure their understanding of presented techniques as well as see how the methods work in real life. Mathematical Asset Management is an excellent book for courses in mathematical finance, actuarial mathematics, financial derivatives, and financial engineering at the upper-undergraduate and graduate levels. It is also a valuable reference for practitioners in banking, insurance, and asset management industries.

This book deals with the management and valuation of energy storage in electric power grids, highlighting the interest of storage systems in grid applications and developing management methodologies based on artificial intelligence tools. The authors highlight the importance of storing electrical energy, in the context of sustainable development, in «smart grids», and discuss multiple services that storing electrical energy can bring. Methodological tools are provided to build an energy management system storage following a generic approach. These tools are based on causal formalisms, artificial intelligence and explicit optimization techniques and are presented throughout the book in connection with concrete case studies.

The aim of this book is to study three essential components of modern finance – Risk Management, Asset Management and Asset and Liability Management, as well as the links that bind them together. It is divided into five parts: Part I sets out the financial and regulatory contexts that explain the rapid development of these three areas during the last few years and shows the ways in which the Risk Management function has developed recently in financial institutions. Part II is dedicated to the underlying theories of Asset Management and deals in depth with evaluation of financial assets and with theories relating to equities, bonds and options. Part III deals with a central theory of Risk Management, the general theory of Value at Risk or VaR, its estimation techniques and the setting up of the methodology. Part IV is the point at which Asset Management and Risk Management meet. It deals with Portfolio Risk Management (the application of risk management methods to private asset management), with an adaptation of Sharpe’s simple index method and the EGP method to suit VaR and application of the APT method to investment funds in terms of behavioural analysis. Part V is the point at which Risk Management and Asset and Liability Management (ALM) meet, and touches on techniques for measuring structural risks within the on and off balance sheet. The book is aimed both at financial professionals and at students whose studies contain a financial aspect. «Esch, Kieffer and Lopez have provided us with a comprehensive and well written treatise on risk. This is a must read, must keep volume for all those who need or aspire to a professional understanding of risk and its management.» —Harry M Markowitz, San Diego, USA

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts – Statistical Models and Methods, Statistical Models and Methods in Survival Analysis, and Reliability and Maintenance. The book is intended for researchers interested in statistical methodology and models useful in survival analysis, system reliability and statistical testing for censored and non-censored data.

Most of the reliability literature is directed towards non repairable systems, that is, systems that fail are discarded. This book is mainly dedicated towards providing coverage to the reliability modeling and analysis of repairable systems that are repaired and not replaced when they fail. Most of the equipment – mechanical or otherwise -are repairable and are subjected to maintenance actions- reactive or proactive- at various levels. Maintenance actions are carried out either to preserve a system or to renovate it to a specified functionable state. Maintenance actions are also characterized by the degree (perfect or imperfect) to which a system can be restored, i.e., to an ‘as good as new condition’ (AGAN), or ‘as bad as old condition’ (ABAO). Mathematically perfect repair is modeled using a renewal process (RP). Since it represents much idealized situation, this model has restricted applications in the analysis of repairable systems. At the other extreme, the ABAO repair is mathematically modelled using a Non-Homogenous Poisson Process (NHPP). These assumptions are very unrealistic for probabilistic modeling and leads to major distortions in statistical analysis. This unique book provides a comprehensive framework for the modeling and analysis of repairable systems considering both the non- parametric and parametric approaches to deal with the failure data. The book presents MCF based non-parametric approach with several illustrative examples and the generalized renewal process (GRP) based arithmetic reduction of age (ARA) models along with its applications to the systems failure data from aviation industry. The book also covers various multi-criteria decision-making (MCDM), integrated with repairable systems reliability analysis models to provide a much better insight into imperfect repair and maintenance data analysis. A complete chapter on an integrated framework for procurement process is added which will of a great assistance to the readers in enhancing the potential of their respective organization. This book also presents FMEA methods tailored for GRP based repairs. This text has primarily emerged from the industrial experience and research work of the authors. A number of illustrations have been included to make the subject lucid and vivid even to the readers who are relatively new to this area. Besides, various examples have been provided to display the applicability of presented models and methodologies to assist the readers in applying the concepts presented in this book.

Recent advances in science and technology have made modern computing and engineering systems more powerful and sophisticated than ever. The increasing complexity and scale imply that system reliability problems not only continue to be a challenge but also require more efficient models and solutions. This is the first book systematically covering the state-of-the-art binary decision diagrams and their extended models, which can provide efficient and exact solutions to reliability analysis of large and complex systems. The book provides both basic concepts and detailed algorithms for modelling and evaluating reliability of a wide range of complex systems, such as multi-state systems, phased-mission systems, fault-tolerant systems with imperfect fault coverage, systems with common-cause failures, systems with disjoint failures, and systems with functional dependent failures. These types of systems abound in safety-critical or mission-critical applications such as aerospace, circuits, power systems, medical systems, telecommunication systems, transmission systems, traffic light systems, data storage systems, and etc. The book provides both small-scale illustrative examples and large-scale benchmark examples to demonstrate broad applications and advantages of different decision diagrams based methods for complex system reliability analysis. Other measures including component importance and failure frequency are also covered. A rich set of references is cited in the book, providing helpful resources for readers to pursue further research and study of the topics. The target audience of the book is reliability and safety engineers or researchers. The book can serve as a textbook on system reliability analysis. It can also serve as a tutorial and reference book on decision diagrams, multi-state systems, phased-mission systems, and imperfect fault coverage models.